 to theCUBE here at the Stanford Excel Partners Symposium, 17th annual, where the theme this year is the modern enterprise. I'm Jeff Kelly with Wikimon. I'm joined now with our next guest from a company called Qualtrics, Ryan Smith, CEO and his brother, Jared Smith, president, welcome guys to theCUBE. Thank you. So why don't we kind of start off, help us understand what Qualtrics is all about. My understanding is around real time research and analytics and kind of give us a primer on what you guys are up to. You know, we're an online, we built a cloud-based platform that helps organizations gather insights to do it yourself tool where, you know, anyone from sophisticated PhD or an intern can go on throughout the organization and gather real time feedback. We think it's absolutely critical that, you know, organizations are gathering data and becoming data driven and we're helping them do that. So it's, talk about some of the customers, your clients you serve, are they across industries? Do you focus on a vertical or? So starting out, primarily, we focused entirely in the academic market. So we've got, you know, every major business school will have, you know, 1,000 Qualtrics users doing a ton of different things on the platform. And in about 2008, 2009, we started focusing on the enterprise. So we have over 5,000 enterprises now. So 1,300 universities and, you know, 5,000 enterprise spanning. I think we just signed up our 200 financial services organizations. We've got the cruise lines, the travel industry, sports teams, pretty much anyone that's got a question or needs to collect data, which we believe everyone does and every organization does, should be on Qualtrics. So, Jared, tell us a little bit about kind of how you came to tackle this problem. What kind of was the, what's your why? Why did you guys decide that this was a problem that needed a new solution? Kind of this type of collecting data, finding answers to questions you didn't know. It was all done offline. And so that's when we started and it was painful. So you would have basically a paper-based survey. Somebody'd stop you in a mall or call you on the phone. They'd say, you know, what do you think of this? You'd say B. You didn't know what you were saying, B. They'd flip to page 32, ask question 71, and then they'd flip back somewhere else. And so if that's the way research was done, you could never do analytics on the fly. You could never do really smart adaptations. And so just moving it online solved a huge amount of problems within the research space. And that's what led us initially to tackle that. Then you do 10 years of innovation on top of that and you end up in a very different spot. Right, so tell us a little bit about that innovation and some of the things that have happened with the consumer web and some of the underlying data, processing and storage technologies and analytics. How has that impacted your business? You guys have been around for a while now. So what's kind of, how has the evolution of the technology kind of impacted how you guys go about doing your job and delivering value to your clients? Well it certainly makes it easier to create products but what, as companies become more data driven, their ability to drive more contextual research is becoming more powerful. So why would I ever ask you a question I've already asked you in the past and I know you? And if somebody's doing that, they're not using our stuff. So it's kind of understanding some of those best practices. If I already know your age, why ask you again? Ah, I see, so that's something you can, in the past, it was really, it was totally kind of out of context. You wouldn't know what you've asked before and it would be very difficult, I would imagine, to kind of compare past results to current results and things like that. Yeah, and if you take it a step further from, I've already got that data, how do you take the data that we're collecting and making it, really turning it into insights so that it's actionable and you're doing something with it and part of that involves integrating into existing platforms that are available and every organization's trying to become more data driven. I mean, ultimately they want to be right and there's one way to do it is to do that, make decisions based on data and not based on opinions a lot of times and to do that, the data is there, you're collecting it. A great example of this, we've got one customer who when they purchase or they go through, it's a famous travel client, they'll have five data points on a customer. By the time they go through and do a Qualtrics survey or transaction where they're gathering feedback, you might have 30 data points. So combining that, there's 35 and then taking that and automatically throwing that into their CRM platform so that there's a score or some sort of mechanism makes the whole process more intelligent and that's exactly what Jared's describing there is leveraging prior data, existing data and merging it together to gather insights. Right, so as we kind of cover the big data space we're seeing a lot of the value really comes when you start bringing in different types of data or maybe different sources. Do you guys work with your clients to help them kind of correlate some of the insights you find with things that they might be seeing in the market or things they might be seeing in other parts of their business? How do you kind of put kind of the insights that you guys help your clients see? How do you help put that into context and some of the other things that are happening in their organization and out in the market at large? Yeah, so we just had a great example of this. We just launched a new product called Site Intercept where it's targeting websites and you're able to intercept people the days of going to a website and right when you get there it says, hey, how's your experience? It's like, look, I just got here, right? I mean, everyone hates that. So we've integrated with a lot of the analytics platforms on the website and so they're tracking some data and then we've got data and we're actually combining the two and being able to target people intelligently. Like, look, we haven't seen you in six months. What's going on? Are you haven't logged in to play fantasy football? You know? Any other data that they've got in triggering an action and then pulling that back down and combining it and do an easy way to analyze. And that's one of the things that we've worked hard at is taking the sophistication out of the analytics side of it. And I think that there's a, you know, that's an area where we're just starting to really make a dent and people are starting to catch on that, look, it's not this hard anymore. Right, that's definitely actually one of the themes I'm seeing here at this event is kind of the application providers trying to obscure some of the complexity underneath to make it possible for, you know, non-data scientists and others to really start to understand their data and take action on that insight. So I wonder, could you talk a little bit about how you actually go about doing that in terms of maybe your design philosophy in terms of how you deliver some of these analytics? How do you actually interact with the end user? Who I imagine, in most cases, is a business user, not necessarily somebody who's got deep statistical skills. How do you kind of make it accessible to some of your clients? Good. I think that, you know, is as far as interacting with the end user, I mean, we've been doing this for a long time, right? I think that if you look at what we were able to do in the academic space, you know, we've got, with the university, there's a thousand users and it could be, you know, a sophisticated PhD who's trying to, you know, study interrupted decision making or some sort of cutting edge research project and then you might have an intern or an undergraduate who's looking to assess where their next fraternity party's going to be, right? So we've really built a platform that allows every possible use case and that's been tried and it's been tested and we've been really close to the customer throughout the whole process. But I think that if you just take a step back and say, you know, what are people trying to do? How do we make it easy for them? And I think with technology, especially over the last five or six years, it's, we're able to do things that we couldn't have done when we first started, you know, in a basement 10 years ago. Right. And I think Jared's probably got a little more insights around making this application. Yeah, well, Jared, I wanted to touch a little bit on the company itself. So you've been around for a little while. You've got about, I think you've raised about $70 million, is that right? Between Excel and Sequoia. So tell us about kind of the state of the company, where you guys are in terms of, you know, kind of staffing and really kind of building the culture internally and where you are there. All up and to the right. And so since taking the funding and well before, everything is just trending up as a mass account. So we're, you know, we're more than doubling in employees every year, clients, you know, same equation, it's that magical spot where almost everything we focus on is just how to scale it. So talk about this event a little bit in some, and you know, there's a lot of entrepreneurs here, a lot of them play in the data space. Talk about the kind of this event and kind of maybe a little bit more big picture. What's the environment like out there for entrepreneurs right now? We're looking to leverage some of the underlying technology we've got in big data, whether it's Hadoop or whatever the case may be, and really build applications on top of that infrastructure. What's the environment in terms of, you know, the available capital, but also, you know, finding the right people to kind of staff up your organization? What is it like out there right now? I think it depends on where you are. So first in terms of the capital, the capital's there always for a good idea. It's just kind of one of the magic of the valley. In terms of, you know, staffing and building an organization, we're actually very insulated from that being out in Utah. But around here, it can be quite hostile with all the talent wars and everything that are going on. And so it's one of the things that we're certainly benefiting might be somewhere else. In terms of, you know, ideas, I think it depends on what space you're in. If you're in enterprise ass at the moment, you know, there's no lack of people looking for good investment. We're a consumer, I hear it's getting a little harder. Indeed. So Ryan, talk a little bit about your experience building the company in terms of the internal culture that you mentioned, how you're growing significantly. You're adding a lot of employees. How do you, you know, as an entrepreneur, how do you keep that culture that you're trying to engender and keep that as you scale up? Our culture's always changing. I mean, we've onboarded 150 employees in a year, right, which is half the company, you know. I can't keep it anymore, I mean, that's one of the things that I realize. But the important thing is that it changes for the better. Right? And I think that if you just keep that in mind, it kind of changes the thought process around it. I think we've constantly been thinking, you know, as our culture evolves, it needs to evolve for the better. And, you know, we're extremely transparent in our organization. One of the most transparent companies I've ever seen. And, you know, I think that we've really shifted the default from being closed to being transparent as opposed to, you know, we're not gonna share this. It's gotta be, why wouldn't we share this? And I think that it's really the only thing that you can do to, one of the only things you can do to make it so that you can onboard that many people and create an organization where everyone's rowing in the same direction is you've gotta arm them with the information that they need to be successful. Because, you know, not everyone can see into our brains or what's going on. And, you know, the more helpful that we can be to over-communicate that, it seems to be the more productive teams are. And they understand, you know, Qualtrics and where Qualtrics is going. But, I think it's the ultimate challenge. And, you know, I think we're doing a great job. I think we're gonna continue to improve at it. Great, well, good advice for any entrepreneurs out there. Ryan and Jared from Qualtrics, thanks so much for joining us. Thanks for having us. I really appreciate it. And thanks for watching. Of course, we'll be right back shortly with more interviews, covering the Stanford Excel Partner Symposium, 17th annual, we're here all day. Please stay tuned.